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基于激素调控基因表达和组织形态学的良性乳腺组织的月经周期和绝经状态分类:一项验证性研究。

Menstrual Phase and Menopausal Status Classification of Benign Breast Tissue Using Hormone-Regulated Gene Expression and Histomorphology: A Validation Study.

机构信息

Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.

School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA.

出版信息

Ann Surg Oncol. 2023 Aug;30(8):5215-5224. doi: 10.1245/s10434-023-13192-1. Epub 2023 Mar 1.

Abstract

BACKGROUND

The validation of breast cancer risk biomarkers in benign breast samples (BBS) is a long-sought goal, hampered by the fluctuation of gene and protein expression with menstrual phase (MP) and menopausal status (MS). Previously, we identified hormone-related gene expression and histomorphology parameters to classify BBS by MS/MP. We now evaluate both together, to validate our prior results.

PATIENTS AND METHODS

BBS were obtained from consenting women (86 premenopausal, 55 postmenopausal) undergoing reduction mammoplasty (RM) or contralateral unaffected breast (CUB) mastectomy. MP/MS was defined using classical criteria for menstrual dates and hormone levels on the day of surgery. BBS gene expression was measured with reverse transcription quantitative polymerase chain reaction (RT-qPCR) for three luteal phase (LP) genes (TNFSF11, DIO2, MYBPC1) and four menopausal genes (PGR, GREB1, TIFF1, CCND1). Premenopausal samples were classified into LP or non-LP, using published histomorphology parameters. Logistic regression and receiver-operator curve analysis was performed to assess area under the curve (AUC) for prediction of MP/MS.

RESULTS

In all 131 women, menopausal genes plus age > 50 years predicted true MS [AUC 0.93, 95% confidence interval (CI) 0.89, 0.97]. Among premenopausal women, high TNFSF11 expression distinguished non-LP from LP samples (AUC 0.80, 95% CI 0.70, 0.91); the addition of histomorphology improved the prediction nonsignificantly (AUC 0.87, 95% CI 0.78, 0.96). In premenopausal subsets, addition of histomorphology improved LP prediction in RM (AUC 0.95, 95% CI 0.87, 1.0), but not in CUB (0.84, 95% CI 0.72, 0.96).

CONCLUSIONS

Expression of five-gene set accurately predicts menopausal status and menstrual phase in BBS, facilitating the development of breast cancer risk biomarkers using large, archived sample repositories.

摘要

背景

在良性乳腺样本(BBS)中验证乳腺癌风险生物标志物是一个长期以来的目标,但由于基因和蛋白质表达随月经周期(MP)和绝经状态(MS)而波动,这一目标一直难以实现。此前,我们已经确定了与激素相关的基因表达和组织形态学参数,以便根据 MS/MP 对 BBS 进行分类。现在,我们同时评估这两个因素,以验证我们之前的结果。

患者和方法

本研究纳入了 86 例接受缩乳术(RM)或对侧未受影响乳房(CUB)乳房切除术的绝经前和 55 例绝经后女性,她们均签署了同意书。MP/MS 是根据月经日期和手术当天的激素水平的经典标准来定义的。通过逆转录定量聚合酶链反应(RT-qPCR)测量 BBS 的三个黄体期(LP)基因(TNFSF11、DIO2、MYBPC1)和四个绝经基因(PGR、GREB1、TIFF1、CCND1)的基因表达。使用已发表的组织形态学参数,将绝经前样本分为 LP 或非 LP。进行逻辑回归和接收者操作特征曲线分析,以评估曲线下面积(AUC)在预测 MP/MS 中的作用。

结果

在所有 131 名女性中,绝经基因加年龄>50 岁可以准确预测真实的 MS[AUC 0.93,95%置信区间(CI)0.89,0.97]。在绝经前女性中,高 TNFSF11 表达可将非 LP 与 LP 样本区分开来(AUC 0.80,95%CI 0.70,0.91);添加组织形态学可略微改善预测结果(AUC 0.87,95%CI 0.78,0.96)。在绝经前亚组中,添加组织形态学可改善 RM 中 LP 预测的准确性(AUC 0.95,95%CI 0.87,1.0),但在 CUB 中则不能(0.84,95%CI 0.72,0.96)。

结论

五基因集的表达可准确预测 BBS 的绝经状态和月经周期,这为利用大型存档样本库开发乳腺癌风险生物标志物提供了便利。

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